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The analysis of plant response to water deficits can help us to identify appropriate water-saving and irrigation methods. The goal of this study is to assess the potential of eight indices derived from a modified consumer-grade camera and a thermal camera for monitoring the relative water content (RWC) of maize. The study design was a randomized complete block design with three replications and 16 treatments with four levels of irrigation water percentage based on field capacity (100% Fc, 80% Fc, 60% Fc and 40% Fc), and four levels of nitrogen (without nitrogen, 100 kg N/ha, 200 kg N/ha and 300 kg N/ha) were used. RWC values were used to evaluate the performance of the eight crop water stress indicators. The results showed that the best performance results of the studied vegetation indices were DANS, CTSD and CTCV, respectively. As observed, R2 values were 0.88, 0.76 and 0.67, respectively. HIGHLIGHTS Low-cost modified camera and thermal camera was used to collect images of maize plants.; The performance of Tc-based indicators and vegetation indices for monitoring maize water status was assessed.; High correlations were found between indices based on thermal images with maize water status.; RGRI-Otsu method was used to improve the accuracy of Tc extraction and background elimination.

The objectives of the current study were to implement affordable and non-invasive measurements of infrared thermometry, leaf relative water content (RWC), crop water stress index (CWSI), leaf area index (LAI) from computer vision analysis and seed yield of sunflowers. The experiment was designed as split-plot based on randomized complete blocks with three replications. Treatments were four different levels of deficit irrigation as the main plots and three fertilization treatments were applied as sub-plots. Results showed a significant effect (P ≤ 0.01) of water stress and fertilizer on CWSI during different stages of sunflower growth. Changes in fertilizer amount and type resulted in a change in lower (dTLL) and upper (dTUL) limits of canopy-air temperature difference. A combination of chemical fertilizer with biofertilizer could help to decrease CWSI. From computer vision analysis, the normalized difference red blue index (NDRBI) had a strong linear relationship with RWC and CWSI for sunflowers (R2 of 0.87 and 0.93, respectively) and the normalized difference green blue index (NDGBI) had a linear relationship with seed yield (R2 = 0.79). Therefore, analysis of digital RGB images and CWSI were efficient, non-destructive and low-cost methods to assess crop water status for sunflowers under different irrigation and fertilizer treatments. HIGHLIGHTS The CWSI values were sensitive not only to different irrigation regimes but also to amount and type of fertilizer.; The CWSI can be derived from the plant index (NDRBI) and used for appropriate irrigation scheduling.; A positive correlation was observed between image indices with CWSI and LAI.; Combination of chemical fertilizer with biofertilizer could help to decrease CWSI.

Paying attention to irrigation of corn could have significant attention on water resources. The experiment was carried out to consider the influence of porous capsule irrigation (PCI), surface drip irrigation (DI) and subsurface drip irrigation (SDI) systems under mulch condition on actual evapotranspiration (ETc act), crop coefficients (Kc single and Kc dual), yield and water use efficiency (WUE) of corn in a semi-arid region of Iran. The experiment was arranged in a split-plot design with three irrigation systems as the main-factor and two soil coverage with mulch (M1) and non- mulch (M2) as sub- factor. The results showed that corn ETc act varied significantly with different irrigation systems (P ), and was reported 389.8, 377.0 and 372.8 mm for PCI, DI and SDI systems, respectively. The highest value of Kc average and Kcb (0.82 and 1.22, respectively) and the minimum value of Ke (0.12) were seen in PCI system. The dry and wet biological yield were the highest in (PCI + M1) treatment (29.98 and 107 ton/ ha, respectively), and the lowest dry and wet biological yield were recorded in (DI + M2) treatment (23.19 and 58.54 ton/ha, respectively). The highest WUE (7.89 kg/m3) were recorded in (PCI + M1) treatment. Using PCI system leads to higher biological yield, WUE and IWUE in comparison to DI and SDI systems. Accordingly, PCI system as an alternative to drip irrigation system can be a viable option for water scarce area particularly for smallholder farmers.

Increasing demand for groundwater for agricultural and industrial needs puts pressure on the water table, especially in arid and semiarid climates. In the Kabudar Ahang plain, in Hamedan province, groundwater overexploitation for agricultural and industrial application has increased significantly over recent decades. The InSAR technique is used to monitor the subsidence induced by groundwater overexploitation in the Kabudar Ahang plain from 2003 to 2010. For this purpose, three different Envisat tracks are used. Interferogram stacking and time-series analysis are performed to study the short-term and long-term behavior of the subsidence. Interferogram time-series analysis from 2003 to 2006 estimates an average subsidence of 19 cm per year with a maximum of 25 cm. The maximum rate of 27 and 28 cm per year is estimated from interferogram stacking in 2004 to 2005 and 2007 to 2010, respectively. The results are further compared with the geological and hydrological information to investigate the relation between the subsidence and groundwater level variations. A high correlation is found in areas affected by subsidence and the rate of water level drop in 10 piezometric wells. The results show that a large part of the plain subsides, mostly in the south and southeast where the aquifer is thicker and in the areas with the highest water table dropdown of about 100 m. With the continued use of groundwater resources, subsidence is another hazard in this plain in addition to the sinkholes.

Aim of study: This work summarizes the influence of surface drip irrigation (DI) and subsurface drip irrigation (SDI) systems on corn growth indices and actual evapotranspiration (ETc-act) and its components of plant transpiration (Tp) and soil evaporation (E).Area of study: Karaj, IranMaterial and methods: The experimental soil was loamy. The corn ETc-act of each mini-lysimeter was measured based on the water balance method. The E was measured using two mini-lysimeters and Tp was estimated from the difference between ETc-act and E.Main results: The resulting data showed that the ETc-act was lower under SDI (384.8 mm) than under DI (423.4 mm). The Kcb-m for the corn increased after sowing and peaked during the mid-season stage, with an average value of 0.47, a minimum value of 0.0 and maximum value of 1.52 under DI and 0.53, 0.0 and 1.74 respectively, under SDI. For Ke-m, the average, minimum and maximum values were 0.33, 0.20 and 0.58 under DI and 0.23, 0.15 and 0.46 respectively, under SDI. The biomass yield was much higher under SDI (81.90 ton/ha) than under DI (63.21 ton/ha). Less E and more Tp occurred under SDI than under DI. SDI achived superior WUE (8.32 kg/m3) compared with DI.Research highlights: SDI was superior to DI based on biomass yield, corn height, stem diameter, and leaf area index which contributed to more favorable soil moisture conditions and low weed incidence; Thus, the SDI system is more productive and would better increase WUE than the DI system.

In this study, an experiment was performed to assess and rank different evapotranspiration models. This was done to estimate the daily actual evapotranspiration of corn using a single (Kc-single) and dual (Kc-dual) crop coefficients in the semiarid climate of Karaj, Iran, in 2014. Daily evapotranspiration calculations using one combination-based model, one pan evaporation-based model, nine temperature-based models, ten radiation-based models, and seven mass transfer-based models were compared to the lysimeter measurements. Considering the single-crop coefficient, the Hargreaves-M3 model (RMSE = 1.89 mm/day) in the temperature-based models, the Caprio (1974) model (RMSE = 1.99 mm/day) in the radiation-based models, and the Albrecht (1950) model (RMSE = 4.33 mm/day) in the mass transfer-based models were ranked first place. Moreover, the Hargreaves-M2 model (RMSE = 0.88 mm/day) in the temperature-based models, the Caprio (1974) model (RMSE = 1.17 mm/day) in the radiation-based models, as well as the Albrecht (1950) model (RMSE = 3.76 mm/day) in the mass transfer-based models using the dual-crop coefficient, provided the most accurate estimation of daily corn evapotranspiration as compared to the lysimeter measurements.

The performance of eight empirical equations for estimating ETo at 80 weather stations in Iran is evaluated. The equations assessed are Hargreaves (HGS), Trajkovic (TKC), Berti (BTI), Ravazzani (RZ...

Accelerated soil erosion is considered as one of serious agro-environmental threats to sustainable development all over the word. Tolerable erosion concept is a tool for awareness and assessment of soil erosion status and its economic, social, and environmental hazards. This study was conducted to design a framework for evaluating and identifying spatial patterns of erosion hazard in Haji-Ghushan watershed, based on tolerable erosion concept, by using the SWAT model. The framework was consisted of two parts: the erosion tolerance index (ETI), and the sediment-phosphorous index (SPI) for evaluating onsite and offsite effects of soil erosion, respectively. Four hazard levels were defined for each index. The results of sediment simulation indicated that the maximum rate of erosion belonged to agricultural lands located on steep slopes in the central part of the watershed, and the minimum rate was from forest lands, despite their steep slopes. The map of spatial distribution of erosion hazard showed that, in terms of both onsite and offsite effects, a major part of the watershed (around 65%) had experienced an erosion rate lower than the erosion tolerance threshold; hence, these areas were not faced with erosion hazard. The spatial distribution of the areas exposed to the onsite erosion hazard, however, was differed from those confronted by the offsite erosion hazard. Identified high hazard areas based on the erosion offsite impacts were mainly located in sub-basins close to the watershed outlet where the sediment and phosphorous yield was high due to the high sediment-phosphorous delivery ratio. High hazard areas with high risk of soil degradation and productivity reduction are distributed throughout the watershed, depending on the magnitude of the erosion rate. These findings revealed that, in addition to erosion rate, sediment delivery ratio is also an important parameter in evaluating soil erosion hazard. For achieving the sustainable agro-environment, it is necessary to consider both the onsite and offsite effects of soil erosion to identify the high hazard areas. Also the results showed that the designed framework was capable of identifying the high hazard and hot spot areas well. The findings of this study are useful for officials and policy makers of soil conservation and environmental protection agencies in the region.

Climate change was simulated using the HADCM3 general circulation model and was downscaled using the LARS-WG downscaling model. After downscaling and uncertainty analysis, climatic parameters were generated until year 2090, assuming three emission scenarios A1, B1 and A1B. After fitting an equation for ETo, its future values were calculated for the simulation period. Results indicated an increase in the mean annual ETo under all three scenarios. The highest increase occurred under the A2 scenario and the lowest increase occurred under the B1 scenario. Comparison of monthly ETo values showed that although greenhouse gas emissions in the next 30-year period did not lead to a perceptible increase in ETo but severe long-term increase was predictable. According to predictions, the mean monthly ETo in the [cold months] in different scenarios did not change significantly and much of the increase occurring in the mean annual ETo was due to a significant increase in the monthly ETo in [hot months] of the year.

Urmia Lake, located in north-west of Iran, has been exposed to various threats such as drought, construction of dams, land use changes and increased global temperature. Due to the importance of Urmia Lake, it is feasible to conduct different kinds of studies to identify the problems of its watershed. The main objective of this study was to evaluate SWAT program’s ability to simulate runoff in Urmia Lake watershed with an area of 52000 km. The model was run for the 1980-1997 period. Calibration and validation periods were from 1980 to 1991 and from 1992 to 1997, respectively. The results of calibration for 10% and 85% of hydrometric stations were very good and suitable, respectively. Also, validation results for 25% and 45% of hydrometric stations were very good and suitable, respectively. These results show the high ability of SWAT model to simulate discharges in Urmia Lake watershed. Moreover, some factors influencing inflow to the lake in recent years were evaluated. The outcomes revealed that recent changes (dam cconstructions, climate change and land use change) in the watershed have caused inflow volume to the lake to decrease by 80%. So, if natural management conditions had prevailed in the watershed, the Lake’s conditions would have been much better.

Groundwater extraction is one of the most important criteria of land degradation especially land subsidence in arid and semi-arid areas. Understanding the relationship between water extraction and recharge of groundwater can lead to better watershed management. For the estimation of groundwater recharge in Razan-Ghahavand watershed in Central Iran the Soil and Water Assessment Tools was used. Model calibration was done by using SUFI-2 based on monthly river discharge and annual crop yield, where crop yield was used to better estimate the evapotranspiration term, which consequently increased our knowledge on estimating aquifer recharge. The calibration results were satisfactory: The Nash–Sutcliffe model efficiency ranged from 0.53 to 0.63 for calibration and from 0.42 to 0.72 for validation. The results showed that, although the groundwater level was decreasing about 1 m per year, the groundwater recharge did not change significantly leading to a net withdrawal causing land subsidence over time.

Increased irrigation in the Neishaboor watershed, Iran, during the last few decades has caused serious groundwater depletion, making the development of comprehensive mitigation strategies and tools increasingly important. In this study, SWAT and MODFLOW were employed to integratively simulate surface-water and groundwater flows. SWAT and MODFLOW were iteratively executed to compute spatial and temporal distributions of hydrologic components. The combined SWAT-MODFLOW model was calibrated (2000–2010) and validated (2010–2012) based on streamflow, wheat yield, groundwater extraction, and groundwater-level data. This multi-criteria calibration procedure provided greater confidence for the partitioning of water between soil storage, actual evapotranspiration, and aquifer recharge. The SWAT model provided satisfactory predictions of the hydrologic budget for the watershed outlet. It also provided good predictions of irrigated wheat yield and groundwater extraction. The 10-year mean annual recharge rate estimated using the combined model varied greatly, ranging from 0 to 960 mm, with an average of 176 mm. This result showed good agreement with the independently estimated annual recharge rate from an earlier study. The combined model provides a robust tool for the sustainable planning and management of water resources for areas with stressed aquifers where interaction between groundwater and surface water cannot be easily assessed.

Application of large amounts of mineral and organic fertilizers in intensive agricultural regions of Hamadan–Bahar watershed in western Iran contributes to excessive nutrient loads in soils and groundwater bodies. Groundwater supplies approximately 88% of the water consumed in Hamadan. The objective of this study was to investigate the temporal and spatial variability of nitrate leaching in Hamadan–Bahar watershed. We employed the Soil and Water Assessment Tool (SWAT) to model the amount and dynamics of nitrate leaching from a typical crop rotation in this watershed. The SWAT model was calibrated and validated with uncertainty analysis using SUFI-2 (Sequential Uncertainty Fitting, ver. 2) based on measured daily discharge data from 7 hydrometric stations, wheat and potato yield, and measured daily nitrate at the outlet of the watershed. The calibration using crop yield increases the confidence on soil moisture and evapotranspiration. The calibration (R2 = 0.83, NS = 0.77) and validation (R2 = 0.70, NS = 0.70) results were quite satisfactory for the outlet of watershed. Spatial variations in nitrate leaching were also found to agree reasonably well with measured nitrate concentrations in groundwater (73% overlap based on a defined criterion). Also, nitrate leaching was found to be more significant under potato (Solanum tuberosum L.) rotation (254–361 kg N ha−1 year−1), representing 30–42% of nitrogen applied to the soil. About 36% of Hamadan–Bahar aquifer has a nitrate leaching rate higher than 100 kg N ha−1 year−1. The presented model and its results have the potential to provide a strong base for considering different scenarios to reduce nitrate leaching and suggest a BMP (best management practice) in Hamadan–Bahar watershed.

One of the major causes of groundwater pollution in Hamadan–Bahar aquifer in western Iran is a non-point source pollution resulting from agricultural activities. Withdrawal of over 88% of drinking water from groundwater resources, adds urgency to the studies leading to a better management of water supplies in this region. In this study, the DRASTIC model was used to construct groundwater vulnerability maps based on the “intrinsic” (natural conditions) and “specific” (including management) concepts. As DRASTIC has drawbacks to simulate specific contaminants, we conditioned the rates on measured nitrate data and optimized the weights of the specific model to obtain a nitrate vulnerability map for the region. The performance of the conditioned DRASTIC model improved significantly (R2 = 0.52) over the intrinsic (R2 = 0.12) and specific (R2 = 0.19) models in predicting the groundwater nitrate concentration. Our study suggests that a locally conditioned DRASTIC model is an effective tool for predicting the region’s vulnerability to nitrate pollution. In addition, comparison of groundwater tables between two periods 30 years apart indicated a drawdown of around 50 m in the central plain of the Hamadan–Bahar region. Our interpretation of the vulnerability maps for the two periods showed a polluted zone developing in the central valley requiring careful evaluation and monitoring.